The continual growth in the availability, detail, and wealth of environmental data provides an invaluable asset to improve the characterization of land heterogeneity in Earth system models – a persistent challenge in macroscale models. However, due to the nature of these data (volume and complexity) and computational constraints, these data are underused for global applications. As a proof of concept, this study explores how to effectively and efficiently harness these data in Earth system models over a 1/4° ( ∼ 25km) grid cell in the western foothills of the Sierra Nevada in central California. First, a novel hierarchical multivariate clustering approach (HMC) is introduced that summarizes the high-dimensional environmental data space into hydrologically interconnected representative clusters (i.e., tiles). These tiles and their associated properties are then used to parameterize the sub-grid heterogeneity of the Geophysical Fluid Dynamics Laboratory (GFDL) LM4-HB land model. To assess how this clustering approach impacts the simulated water, energy, and carbon cycles, model experiments are run using a series of different tile configurations assembled using HMC. The results over the test domain show that (1) the observed similarity over the landscape makes it possible to converge on the macroscale response of the fully distributed model with around 300 sub-grid land model tiles; (2) assembling the sub-grid tile configuration from available environmental data can have a large impact on the macroscale states and fluxes of the water, energy, and carbon cycles; for example, the defined subsurface connections between the tiles lead to a dampening of macroscale extremes; (3) connecting the fine-scale grid to the model tiles via HMC enables circumvention of the classic scale discrepancies between the macroscale and field-scale estimates; this has potentially significant implications for the evaluation and application of Earth system models.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/hess-22-3311-2018","usgsCitation":"Chaney, N.W., Van Huijgevoort, M.H., Shevliakova, E., Malyshev, S., Milly, P.C., Gauthier, P., and Sulman, B.N., 2018, Harnessing big data to rethink land heterogeneity in Earth system models: Hydrology and Earth System Sciences, v. 22, p. 3311-3330, https://doi.org/10.5194/hess-22-3311-2018.","productDescription":"20 p.","startPage":"3311","endPage":"3330","ipdsId":"IP-090830","costCenters":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"links":[{"id":468658,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/hess-22-3311-2018","text":"Publisher Index Page"},{"id":358546,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"22","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","scienceBaseUri":"5c10a99ae4b034bf6a7e535d","contributors":{"authors":[{"text":"Chaney, Nathaniel W.","contributorId":169242,"corporation":false,"usgs":false,"family":"Chaney","given":"Nathaniel","email":"","middleInitial":"W.","affiliations":[{"id":25453,"text":"Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA","active":true,"usgs":false}],"preferred":false,"id":749025,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Van Huijgevoort, Marjolein H. J.","contributorId":209888,"corporation":false,"usgs":false,"family":"Van Huijgevoort","given":"Marjolein","email":"","middleInitial":"H. J.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749026,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Shevliakova, Elena","contributorId":201589,"corporation":false,"usgs":false,"family":"Shevliakova","given":"Elena","email":"","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749027,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Malyshev, Sergey","contributorId":201588,"corporation":false,"usgs":false,"family":"Malyshev","given":"Sergey","affiliations":[{"id":36211,"text":"GFDL/NOAA","active":true,"usgs":false}],"preferred":false,"id":749028,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Milly, Paul C. D. 0000-0003-4389-3139 cmilly@usgs.gov","orcid":"https://orcid.org/0000-0003-4389-3139","contributorId":176836,"corporation":false,"usgs":true,"family":"Milly","given":"Paul","email":"cmilly@usgs.gov","middleInitial":"C. D.","affiliations":[{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true},{"id":37778,"text":"WMA - Integrated Modeling and Prediction Division","active":true,"usgs":true}],"preferred":false,"id":749024,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Gauthier, Paul P. G.","contributorId":209889,"corporation":false,"usgs":false,"family":"Gauthier","given":"Paul P. G.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749029,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Sulman, Benjamin N. 0000-0002-3265-6691","orcid":"https://orcid.org/0000-0002-3265-6691","contributorId":209890,"corporation":false,"usgs":false,"family":"Sulman","given":"Benjamin","email":"","middleInitial":"N.","affiliations":[{"id":7108,"text":"Princeton Univ.","active":true,"usgs":false}],"preferred":false,"id":749030,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70216335,"text":"70216335 - 2018 - Thresholds and hotspots for shrub restoration following a heterogeneous megafire","interactions":[],"lastModifiedDate":"2020-11-12T15:00:59.555625","indexId":"70216335","displayToPublicDate":"2018-06-14T08:54:45","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2602,"text":"Landscape Ecology","active":true,"publicationSubtype":{"id":10}},"title":"Thresholds and hotspots for shrub restoration following a heterogeneous megafire","docAbstract":"Reestablishing foundational plant species through aerial seeding is an essential yet challenging step for restoring the vast semiarid landscapes impacted by plant invasions and wildfire-regime shifts. A key component of the challenge stems from landscape variability and its effects on plant recovery.
We assessed landscape correlates, thresholds, and tipping points for sagebrush presence from fine-scale sampling across a large, heterogeneous area burned the previous year, where we were able to quantify soil surface features that are typically occluded yet can strongly affect recovery patterns.
Hypothesis testing and binary-decision trees were used to evaluate factors affecting initial sagebrush establishment, using 2171 field plots (totaling ~ 2,000,000 m2 sampled) over a 113,000-ha region.
Sagebrush established in 50% of plots where it was seeded, a > 12-fold greater establishment frequency than in unseeded areas. Sagebrush establishment was enhanced in threshold-like ways by elevation (> 1200 m ASL), topographic features that alter heatload and soil water, and by soil-surface features such as “fertile islands” that bore the imprint of pre-fire sagebrush. Sagebrush occupancy had a negative, linear relationship with exotic-annual grass cover and parabolic relationship with perennial bunchgrasses (optimal at 40% cover).
Our approach revealed interactive, ecological relationships such as novel soil-surface effects on first year establishment of sagebrush across the burned landscape, and identified “hot spots” for recovery. The approach could be expanded across sites and years to provide the information needed to explain past seeding successes or failures, and in designing treatments at the landscape scale.
","language":"English","publisher":"Springer","doi":"10.1007/s10980-018-0662-8","usgsCitation":"Germino, M., Barnard, D., Davidson, B., Arkle, R., Pilliod, D., Fisk, M., and Applestein, C., 2018, Thresholds and hotspots for shrub restoration following a heterogeneous megafire: Landscape Ecology, v. 33, p. 1177-1194, https://doi.org/10.1007/s10980-018-0662-8.","productDescription":"18 p.","startPage":"1177","endPage":"1194","ipdsId":"IP-090670","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":380454,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Idaho","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -117.04833984375001,\n 43.197167282501276\n ],\n [\n -116.1474609375,\n 43.197167282501276\n ],\n [\n -116.1474609375,\n 44.008620115415354\n ],\n [\n -117.04833984375001,\n 44.008620115415354\n ],\n [\n -117.04833984375001,\n 43.197167282501276\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2018-06-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Germino, Matthew 0000-0001-6326-7579","orcid":"https://orcid.org/0000-0001-6326-7579","contributorId":218007,"corporation":false,"usgs":true,"family":"Germino","given":"Matthew","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804733,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Barnard, David 0000-0003-1877-3151","orcid":"https://orcid.org/0000-0003-1877-3151","contributorId":218008,"corporation":false,"usgs":true,"family":"Barnard","given":"David","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804734,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Davidson, Bill 0000-0003-1315-479X","orcid":"https://orcid.org/0000-0003-1315-479X","contributorId":218011,"corporation":false,"usgs":true,"family":"Davidson","given":"Bill","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804735,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Arkle, Robert 0000-0003-3021-1389","orcid":"https://orcid.org/0000-0003-3021-1389","contributorId":216339,"corporation":false,"usgs":true,"family":"Arkle","given":"Robert","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804736,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pilliod, David S. 0000-0003-4207-3518","orcid":"https://orcid.org/0000-0003-4207-3518","contributorId":229349,"corporation":false,"usgs":true,"family":"Pilliod","given":"David S.","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804737,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Fisk, Matthew 0000-0002-2250-0116","orcid":"https://orcid.org/0000-0002-2250-0116","contributorId":205749,"corporation":false,"usgs":true,"family":"Fisk","given":"Matthew","email":"","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804738,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Applestein, Cara 0000-0002-7923-8526","orcid":"https://orcid.org/0000-0002-7923-8526","contributorId":205748,"corporation":false,"usgs":true,"family":"Applestein","given":"Cara","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":804739,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70196548,"text":"ofr20181068 - 2018 - A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat)","interactions":[],"lastModifiedDate":"2018-09-25T07:59:14","indexId":"ofr20181068","displayToPublicDate":"2018-06-14T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1068","title":"A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat)","docAbstract":"The North American Bat Monitoring Program (NABat) aims to improve the state of conservation science for all species of bats shared by the United States, Canada, and Mexico. To accomplish this goal, NABat offers guidance and standardized protocols for acoustic monitoring of bats. In this document, “A Guide to Processing Bat Acoustic Data for the North American Bat Monitoring Program (NABat),” we provide general recommendations and specific workflows for the process of identifying bat species from acoustic files recorded using the NABat stationary point and mobile transect acoustic monitoring protocols.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181068","collaboration":"Prepared in cooperation with Wildlife Conservation Society Canada, USDA Forest Service, US Army Corps of Engineers, Illinois Natural History Survey, New York State Department of Environmental Conservation, Colorado Natural Heritage Program, Montana Natural Heritage Program, National Park Service, and Bat Call Identification, Inc.","usgsCitation":"Reichert, B., and Lausen, C., Loeb, S., Weller, T., Allen, R., Britzke, E., Hohoff, T., Siemers, J., Burkholder, B., Herzog, C., and Verant, M., 2018, A guide to processing bat acoustic data for the North American Bat Monitoring Program (NABat): U.S. Geological Survey Open-File Report 2018–1068, 33 p., https://doi.org/10.3133/ofr20181068.","productDescription":"vi, 33 p.","numberOfPages":"43","onlineOnly":"Y","ipdsId":"IP-092559","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":353437,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1068/coverthb2.jpg"},{"id":354992,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1068/ofr20181068.pdf","text":"Report","size":"3.11 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018–1068"}],"contact":"Center Director, Fort Collins Science Center
U.S. Geological Survey
2150 Centre Ave., Bldg. C
Fort Collins, CO 80526-8118
The bedrock geologic map of the Littleton and Lower Waterford quadrangles covers an area of approximately 107 square miles (277 square kilometers) north and south of the Connecticut River in east-central Vermont and adjacent New Hampshire. This map was created as part of a larger effort to produce a new bedrock geologic map of Vermont through the collection of field data at a scale of 1:24,000. A large part of the map area consists of the Bronson Hill anticlinorium, a post-Early Devonian structure that is cored by metamorphosed Cambrian to Devonian sedimentary, volcanic, and plutonic rocks. The northwestern part of the map is divided by the Monroe fault which separates Early Devonian rocks of the Connecticut Valley-Gaspé trough from rocks of the Bronson Hill anticlinorium.
The Bronson Hill anticlinorium is the apex of the Middle Ordovician to earliest-Silurian Bronson Hill magmatic arc that contains the Ammonoosuc Volcanics, Partridge Formation, and Oliverian Plutonic suite, and extends from Maine, down the eastern side of the Connecticut River in New Hampshire, to Long Island Sound. The deformed and partially eroded arc is locally overlain by a relatively thin Silurian section of metasedimentary rocks (Clough Quartzite and Fitch Formation) that thickens to the east. The Silurian section near Littleton is disconformably overlain by a thicker, Lower Devonian section that includes mostly metasedimentary rocks and minor metavolcanic rocks of the Littleton Formation. The Bronson Hill anticlinorium is bisected by a series of northeast-southwest trending Mesozoic normal faults. Primarily among them is the steeply northwest-dipping Ammonoosuc fault that divides older and younger units (upper and lower sections) of the Ammonoosuc Volcanics. The Ammonoosuc Volcanics are lithologically complex and predominantly include interlayered and interfingered rhyolitic to basaltic volcanic and volcaniclastic rocks, as well as lesser amounts of metamorphic and metasedimentary rocks. The Ammonoosuc Volcanics overlies the Albee Formation that consists of interlayered feldspathic sandstone, siltstone, pelite, and slate.
During the Late Ordovician, a series of arc-related plutons intruded the Ammonoosuc Volcanics, including the Whitefield pluton to the east, the Scrag granite of Billing (1937) in the far southeastern corner of the map, the Highlandcroft Granodiorite just to the west of the Ammonoosuc fault, and the Joslin Turn tonalite (just north of the Connecticut River). To the east of the Monroe fault lies the late Silurian Comerford Intrusive Complex, which consists of metamorphosed gabbro, diorite, tonalite, aplitic tonalite, and crosscutting diabase dikes. Abundant mafic dikes of the Comerford Intrusive Complex intruded the Albee Formation and Ammonoosuc Volcanics well east of the Monroe fault.
This report consists of a single geologic map sheet and an online geographic information systems database that includes contacts of bedrock geologic units, faults, outcrops, and structural geologic information.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181087","collaboration":"Prepared in cooperation with the State of Vermont, Vermont Agency of Natural Resources, Vermont Geological Survey, and the State of New Hampshire, Department of Environmental Services, New Hampshire Geological Survey","usgsCitation":"Rankin, D.W., 2018, Bedrock geologic map of the Littleton and Lower Waterford quadrangles, Essex and Caledonia Counties, Vermont, and Grafton County, New Hampshire: U.S. Geological Survey Open-File Report 2018–1087, 1 sheet, scale 1:24,000, https://doi.org/10.3133/ofr20181087.","productDescription":"Sheet: 36.00 x 45.82 inches; Geologic Map: ArcGIS 10.5 zip; Geodatabase; Metadata; Base Map","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-081645","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":354879,"rank":3,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_geologic-map-files.zip","text":"Geologic Map (ArcGIS 10.5)","size":"49.3 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Geologic Map"},{"id":354880,"rank":5,"type":{"id":23,"text":"Spatial Data"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_basemap-files.zip","text":"Base Map","size":"10.8 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Base Map"},{"id":354979,"rank":6,"type":{"id":16,"text":"Metadata"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_littleton-lowerwaterford-xml.zip","text":"Metadata ","size":"67.1 KB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Metadata"},{"id":354876,"rank":2,"type":{"id":26,"text":"Sheet"},"url":"https://pubs.usgs.gov/of/2018/1087/ofr20181087.pdf","text":"Geologic Map","size":"24.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1087"},{"id":354875,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1087/coverthb2.jpg"},{"id":354878,"rank":4,"type":{"id":9,"text":"Database"},"url":"https://pubs.usgs.gov/of/2018/1087/metadata/ofr20181087_database-files.gdb.zip","text":"Database","size":"1.30 MB","linkFileType":{"id":6,"text":"zip"},"linkHelpText":"- Littleton and Lower Waterford, Vermont, and New Hampshire, Geodatabase "}],"country":"United States","state":"New Hampshire, Vermont","county":"Caledonia County, Grafton County, Essex County","otherGeospatial":"Littleton Quadrangle, Lower Waterford Quadrangle","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72,\n 44.25\n ],\n [\n -71.75,\n 44.25\n ],\n [\n -71.75,\n 44.375\n ],\n [\n -72,\n 44.375\n ],\n [\n -72,\n 44.25\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
The Collaboratory for the Study of Earthquake Predictability (CSEP; Jordan, 2006) carries out fully prospective tests of earthquake forecasts, using fixed and standardized statistical tests and authoritative data sets, to assess the predictive skill of forecast models and to make objective comparisons between models. CSEP conducts prospective experiments at four testing centers around the world, at which more than 400 models and model versions are currently under evaluation. These models include a range of methods and scales from long‐term global earthquake forecasts to short‐term regional forecasts used for Operational Earthquake Forecasting (OEF). CSEP has also conducted retrospective tests and developed new testing methods in its quest to answer fundamental scientific questions, improve seismic hazard assessments, and develop new forecast methods for OEF.
","language":"English","publisher":"Seismological Society of America","doi":"10.1785/0220180161","usgsCitation":"Michael, A.J., and Werner, M.J., 2018, Preface to the Focus Section on the Collaboratory for the Study of Earthquake Predictability (CSEP): New results and future directions: Seismological Research Letters, v. 89, no. 4, p. 1226-1228, https://doi.org/10.1785/0220180161.","productDescription":"3 p.","startPage":"1226","endPage":"1228","ipdsId":"IP-098396","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":468662,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://research-information.bris.ac.uk/en/publications/5ef252d7-aa19-4039-bc43-051e520e7e29","text":"External Repository"},{"id":360739,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"89","issue":"4","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-13","publicationStatus":"PW","scienceBaseUri":"5c5022c5e4b0708288f7e826","contributors":{"authors":[{"text":"Michael, Andrew J. 0000-0002-2403-5019 michael@usgs.gov","orcid":"https://orcid.org/0000-0002-2403-5019","contributorId":1280,"corporation":false,"usgs":true,"family":"Michael","given":"Andrew","email":"michael@usgs.gov","middleInitial":"J.","affiliations":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true},{"id":234,"text":"Earthquake Hazards Program","active":true,"usgs":true}],"preferred":true,"id":754957,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Werner, Maximillian J.","contributorId":211807,"corporation":false,"usgs":false,"family":"Werner","given":"Maximillian","email":"","middleInitial":"J.","affiliations":[{"id":38325,"text":"University of Bristol, UK","active":true,"usgs":false}],"preferred":false,"id":754958,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70196670,"text":"fs20183027 - 2018 - National Satellite Land Remote Sensing Data Archive","interactions":[{"subject":{"id":70049060,"text":"fs20133100 - 2013 - National Satellite Land Remote Sensing Data Archive","indexId":"fs20133100","publicationYear":"2013","noYear":false,"title":"National Satellite Land Remote Sensing Data Archive"},"predicate":"SUPERSEDED_BY","object":{"id":70196670,"text":"fs20183027 - 2018 - National Satellite Land Remote Sensing Data Archive","indexId":"fs20183027","publicationYear":"2018","noYear":false,"title":"National Satellite Land Remote Sensing Data Archive"},"id":1}],"lastModifiedDate":"2018-09-25T06:34:15","indexId":"fs20183027","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":313,"text":"Fact Sheet","code":"FS","onlineIssn":"2327-6932","printIssn":"2327-6916","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-3027","title":"National Satellite Land Remote Sensing Data Archive","docAbstract":"The National Satellite Land Remote Sensing Data Archive is managed on behalf of the Secretary of the Interior by the U.S. Geological Survey’s Earth Resources Observation and Science Center. The Land Remote Sensing Policy Act of 1992 (51 U.S.C. §601) directed the U.S. Department of the Interior to establish a permanent global archive consisting of imagery over land areas obtained from satellites orbiting the Earth. The law also directed the U.S. Department of the Interior, delegated to the U.S. Geological Survey, to ensure proper storage and preservation of imagery, and timely access for all parties. Since 2008, these images have been available at no cost to the user.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/fs20183027","usgsCitation":"Faundeen, J.L., and Longhenry, R., 2018, National Satellite Land Remote Sensing Data Archive: U.S. Geological Survey Fact Sheet 2018–3027, 2 p., https://doi.org/10.3133/fs20183027. [Supersedes USGS Fact Sheet 2013–3100.]","productDescription":"2 p.","onlineOnly":"Y","ipdsId":"IP-096390","costCenters":[{"id":222,"text":"Earth Resources Observation and Science (EROS) Center","active":true,"usgs":true}],"links":[{"id":354967,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/fs/2018/3027/fs20183027.pdf","text":"Report","size":"10.1 MB","linkFileType":{"id":1,"text":"pdf"},"description":"FS 2018–3027"},{"id":354966,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/fs/2018/3027/coverthb2.jpg"}],"contact":"Director, Earth Resources Observation and Science Center
U.S. Geological Survey
47914 252nd Street
Sioux Falls, SD 57198
We reexamine the geometry of the causative fault structure of the 1989 moment-magnitude-6.9 Loma Prieta earthquake in central California, using seismic-reflection, earthquake-hypocenter, and magnetic data. Our study is prompted by recent interpretations of a two-part dip of the San Andreas Fault (SAF) accompanied by a flower-like structure in the Coachella Valley, in southern California. Initially, the prevailing interpretation of fault geometry in the vicinity of the Loma Prieta earthquake was that the mainshock did not rupture the SAF, but rather a secondary fault within the SAF system, because network locations of aftershocks defined neither a vertical plane nor a fault plane that projected to the surface trace of the SAF. Subsequent waveform cross-correlation and double-difference relocations of Loma Prieta aftershocks appear to have clarified the fault geometry somewhat, with steeply dipping faults in the upper crust possibly connecting to the more moderately southwest-dipping mainshock rupture in the middle crust. Examination of steep-reflection data, extracted from a 1991 seismic-refraction profile through the Loma Prieta area, reveals three robust fault-like features that agree approximately in geometry with the clusters of upper-crustal relocated aftershocks. The subsurface geometry of the San Andreas, Sargent, and Berrocal Faults can be mapped using these features and the aftershock clusters. The San Andreas and Sargent Faults appear to dip northeastward in the uppermost crust and change dip continuously toward the southwest with depth. Previous models of gravity and magnetic data on profiles through the aftershock region also define a steeply dipping SAF, with an initial northeastward dip in the uppermost crust that changes with depth. At a depth 6 to 9 km, upper-crustal faults appear to project into the moderately southwest-dipping, planar mainshock rupture. The change to a planar dipping rupture at 6–9 km is similar to fault geometry seen in the Coachella Valley.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181093","usgsCitation":"Zhang, E., Fuis, G.S., Catchings, R.D., Scheirer, D.S., Goldman, M., and Bauer, K., 2018, Reexamination of the subsurface fault structure in the vicinity of the 1989 moment-magnitude-6.9 Loma Prieta earthquake, central California, using steep-reflection, earthquake, and magnetic data: U.S. Geological Survey Open-File Report 2018–1093, 35 p., https://doi.org/10.3133/ofr20181093.","productDescription":"v; 35 p.","onlineOnly":"Y","ipdsId":"IP-097280","costCenters":[{"id":237,"text":"Earthquake Science Center","active":true,"usgs":true}],"links":[{"id":355009,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1093/coverthb.jpg"},{"id":355010,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1093/ofr20181093.pdf","text":"Report","size":"8.5 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1093"}],"country":"United States","state":"California","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -121.92214965820311,\n 36.97128966642495\n ],\n [\n -121.75804138183594,\n 36.97128966642495\n ],\n [\n -121.75804138183594,\n 37.2\n ],\n [\n -121.92214965820311,\n 37.2\n ],\n [\n -121.92214965820311,\n 36.97128966642495\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Contact Information, Menlo Park, Calif.
Office—Earthquake Science Center
U.S. Geological Survey
345 Middlefield Road, MS 977
Menlo Park, CA 94025
https://earthquake.usgs.gov/
Effective methods to control invasive Sea Lampreys Petromyzon marinus in the Laurentian Great Lakes often rely on knowledge of the timing of the Sea Lamprey spawning migration, which has previously been characterized using data gathered from traps. Most assessment traps are located many kilometers upstream from the river mouth, so less is known about when Sea Lampreys enter spawning streams and which environmental cues trigger their transition from lakes to rivers. To decide how to develop barriers and traps that target Sea Lampreys when they enter a stream, the stream entry of Sea Lampreys into a Lake Huron tributary during 2 years was assessed using dual‐frequency identification sonar (DIDSON). Sea Lampreys entered the stream in low densities when temperatures first reached 4°C, which was up to 6 weeks and a mean of 4 weeks earlier than when they were first captured in traps located upstream. The probability of stream entry was significantly affected by stream temperature and discharge, and stream entry timing peaked when stream temperatures rose to 12°C and discharge was high. Examination of the entry at a finer temporal resolution (i.e., minutes) indicated that Sea Lampreys did not exhibit social behavior (e.g., shoaling) during stream entry. Our findings indicate that Sea Lampreys may be vulnerable to alternative trap types near river mouths and hydraulic challenges associated with traditional traps. Also, seasonal migration barriers near stream mouths may need to be installed soon after ice‐out to effectively block the entire adult Sea Lamprey cohort from upstream spawning habitat.
","language":"English","publisher":"American Fisheries Society","doi":"10.1002/tafs.10052","usgsCitation":"McCain, E.L., Johnson, N., Hrodey, P.J., and Pangle, K.L., 2018, Characterization of Sea Lamprey stream entry using dual‐frequency identification sonar: Transactions of the American Fisheries Society, v. 147, no. 3, p. 514-524, https://doi.org/10.1002/tafs.10052.","productDescription":"11 p.","startPage":"514","endPage":"524","ipdsId":"IP-094521","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":355013,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Michigan","otherGeospatial":"Ocqueoc River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -84.35028076171875,\n 45.377231681380145\n ],\n [\n -83.87786865234375,\n 45.377231681380145\n ],\n [\n -83.87786865234375,\n 45.67932023569538\n ],\n [\n -84.35028076171875,\n 45.67932023569538\n ],\n [\n -84.35028076171875,\n 45.377231681380145\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"147","issue":"3","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-22","publicationStatus":"PW","scienceBaseUri":"5b46e56ae4b060350a15d133","contributors":{"authors":[{"text":"McCain, Erin L.","contributorId":205577,"corporation":false,"usgs":false,"family":"McCain","given":"Erin","email":"","middleInitial":"L.","affiliations":[{"id":37116,"text":"Department of Biology, Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":737885,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737884,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hrodey, Peter J.","contributorId":205578,"corporation":false,"usgs":false,"family":"Hrodey","given":"Peter","email":"","middleInitial":"J.","affiliations":[{"id":6599,"text":"U.S. Fish and Wildlife Service, Marquette Biological Station","active":true,"usgs":false}],"preferred":false,"id":737886,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pangle, Kevin L.","contributorId":205579,"corporation":false,"usgs":false,"family":"Pangle","given":"Kevin","email":"","middleInitial":"L.","affiliations":[{"id":37116,"text":"Department of Biology, Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":737887,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197607,"text":"70197607 - 2018 - A distributed pipeline for DIDSON data processing","interactions":[],"lastModifiedDate":"2018-06-14T09:43:00","indexId":"70197607","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"A distributed pipeline for DIDSON data processing","docAbstract":"Technological advances in the field of ecology allow data on ecological systems to be collected at high resolution, both temporally and spatially. Devices such as Dual-frequency Identification Sonar (DIDSON) can be deployed in aquatic environments for extended periods and easily generate several terabytes of underwater surveillance data which may need to be processed multiple times. Due to the large amount of data generated and need for flexibility in processing, a distributed pipeline was constructed for DIDSON data making use of the Hadoop ecosystem. The pipeline is capable of ingesting raw DIDSON data, transforming the acoustic data to images, filtering the images, detecting and extracting motion, and generating feature data for machine learning and classification. All of the tasks in the pipeline can be run in parallel and the framework allows for custom processing. Applications of the pipeline include monitoring migration times, determining the presence of a particular species, estimating population size and other fishery management tasks.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"2017 IEEE International Conference on Big Data","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceDate":"December 11-14, 2017","conferenceLocation":" Boston, MA","language":"English","publisher":"IEEE","doi":"10.1109/BigData.2017.8258458","usgsCitation":"Li, L., Danner, T., Eickholt, J., McCann, E.L., Pangle, K., and Johnson, N., 2018, A distributed pipeline for DIDSON data processing, in 2017 IEEE International Conference on Big Data, Boston, MA, December 11-14, 2017, https://doi.org/10.1109/BigData.2017.8258458.","ipdsId":"IP-092643","costCenters":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"links":[{"id":355011,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e56ae4b060350a15d131","contributors":{"authors":[{"text":"Li, Liling","contributorId":205580,"corporation":false,"usgs":false,"family":"Li","given":"Liling","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":737889,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Danner, Tyler","contributorId":205581,"corporation":false,"usgs":false,"family":"Danner","given":"Tyler","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":737890,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Eickholt, Jesse","contributorId":205582,"corporation":false,"usgs":false,"family":"Eickholt","given":"Jesse","email":"","affiliations":[{"id":13588,"text":"Central Michigan University","active":true,"usgs":false}],"preferred":false,"id":737891,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"McCann, Erin L.","contributorId":195636,"corporation":false,"usgs":false,"family":"McCann","given":"Erin","email":"","middleInitial":"L.","affiliations":[],"preferred":false,"id":737892,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Pangle, Kevin","contributorId":195637,"corporation":false,"usgs":false,"family":"Pangle","given":"Kevin","affiliations":[],"preferred":false,"id":737893,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Johnson, Nicholas S. 0000-0002-7419-6013 njohnson@usgs.gov","orcid":"https://orcid.org/0000-0002-7419-6013","contributorId":150983,"corporation":false,"usgs":true,"family":"Johnson","given":"Nicholas S.","email":"njohnson@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737888,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70197611,"text":"70197611 - 2018 - Rapid 3-D analysis of rockfalls","interactions":[],"lastModifiedDate":"2018-06-13T12:35:22","indexId":"70197611","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1728,"text":"GSA Today","active":true,"publicationSubtype":{"id":10}},"title":"Rapid 3-D analysis of rockfalls","docAbstract":"Recent fatal and damaging rockfalls in Yosemite National Park indicate the need for rapid response data collection methods to inform public safety and assist with management response. Here we show the use of multiple-platform remote sensing methods to rapidly capture pertinent data needed to inform management and the public following a several large rockfalls from El Capitan cliff in Yosemite Valley, California.","language":"English","publisher":"Geological Society of America","doi":"10.1130/GSATG374GW.1","usgsCitation":"Stock, G.M., Guerin, A., Avdievitch, N.N., Collins, B.D., and Jaboyedoff, M., 2018, Rapid 3-D analysis of rockfalls: GSA Today, v. 28, 2 p., https://doi.org/10.1130/GSATG374GW.1.","productDescription":"2 p.","ipdsId":"IP-097512","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"links":[{"id":488014,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1130/gsatg374gw.1","text":"Publisher Index Page"},{"id":355008,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"28","publishingServiceCenter":{"id":14,"text":"Menlo Park PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-12","publicationStatus":"PW","scienceBaseUri":"5b46e56ae4b060350a15d12f","contributors":{"authors":[{"text":"Stock, Greg M.","contributorId":202873,"corporation":false,"usgs":false,"family":"Stock","given":"Greg","email":"","middleInitial":"M.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":737902,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Guerin, A.","contributorId":205585,"corporation":false,"usgs":false,"family":"Guerin","given":"A.","email":"","affiliations":[{"id":37117,"text":"University of Lausanne (Switzerland)","active":true,"usgs":false}],"preferred":false,"id":737903,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Avdievitch, Nikita N.","contributorId":143693,"corporation":false,"usgs":false,"family":"Avdievitch","given":"Nikita","email":"","middleInitial":"N.","affiliations":[{"id":15304,"text":"University of Tubingen, Wilhelmstrasse 56, Tugingen, GER 72076","active":true,"usgs":false}],"preferred":false,"id":737904,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Collins, Brian D. 0000-0003-4881-5359 bcollins@usgs.gov","orcid":"https://orcid.org/0000-0003-4881-5359","contributorId":149278,"corporation":false,"usgs":true,"family":"Collins","given":"Brian","email":"bcollins@usgs.gov","middleInitial":"D.","affiliations":[{"id":186,"text":"Coastal and Marine Geology Program","active":true,"usgs":true},{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":737901,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Jaboyedoff, Michel","contributorId":205586,"corporation":false,"usgs":false,"family":"Jaboyedoff","given":"Michel","affiliations":[{"id":37117,"text":"University of Lausanne (Switzerland)","active":true,"usgs":false}],"preferred":false,"id":737905,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70197616,"text":"70197616 - 2018 - Nonbreeding duck use at Central Flyway National Wildlife Refuges","interactions":[],"lastModifiedDate":"2018-06-14T09:37:43","indexId":"70197616","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2287,"text":"Journal of Fish and Wildlife Management","active":true,"publicationSubtype":{"id":10}},"title":"Nonbreeding duck use at Central Flyway National Wildlife Refuges","docAbstract":"Within the U.S. portion of the Central Flyway, the U.S. Fish and Wildlife Service manages waterfowl on numerous individual units (i.e., Refuges) within the National Wildlife Refuge System. Presently, the extent of waterfowl use that Refuges receive and the contribution of Refuges to waterfowl populations (i.e., the proportion of the Central Flyway population registered at each Refuge) remain unassessed. Such an evaluation would help determine to what extent Refuges support waterfowl relative to stated targets, aid in identifying species requiring management attention, inform management targets, and improve fiscal efficiencies. Using historic monitoring data (1954–2008), we performed this assessment for 23 Refuges in Texas, New Mexico, Oklahoma, Kansas, and Nebraska during migration and wintering months (October–March). We examined six dabbling ducks and two diving ducks, plus all dabbling ducks and all diving ducks across two periods (long-term [all data] and short-term [last 10 October–March periods]). Individual Refuge use was represented by the sum of monthly duck count averages for October–March. We used two indices of Refuge contribution: peak contribution and January contribution. Peak contribution was the highest monthly count average for each October–March period divided by the indexed population total for the Central Flyway in the corresponding year; January contribution used the January count average divided by the corresponding population index. Generally, Refuges in Kansas, Nebraska, and New Mexico recorded most use and contribution for mallards Anas platyrhynchos. Refuges along the Texas Gulf Coast recorded most use and contribution for other dabbling ducks, with Laguna Atascosa and Aransas (including Matagorda Island) recording most use for diving ducks. The long-term total January contribution of the assessed Refuges to ducks wintering in the Central Flyway was greatest for green-winged teal Anas creccawith 35%; 12–15% for American wigeon Mareca americana, gadwall Mareca strepera, and northern pintail Anas acuta; and 7–8% for mallard and mottled duck Anas fulvigula. Results indicated that the reliance on the National Wildlife Refuge System decreased for these ducks, with evidence suggesting that, for several species, the assessed Refuges may be operating at carrying capacity. Future analyses could be more detailed and informative were Refuges to implement a single consistent survey methodology that incorporated estimations of detection bias in the survey process, while concomitantly recording habitat metrics on and neighboring each Refuge.
","language":"English","publisher":"U.S. Fish and Wildlife Service","doi":"10.3996/042017-JFWM-033","usgsCitation":"Andersson, K., Davis, C.A., Harris, G., and Haukos, D.A., 2018, Nonbreeding duck use at Central Flyway National Wildlife Refuges: Journal of Fish and Wildlife Management, v. 9, no. 1, p. 45-64, https://doi.org/10.3996/042017-JFWM-033.","productDescription":"20 p.","startPage":"45","endPage":"64","ipdsId":"IP-079449","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":468665,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3996/042017-jfwm-033","text":"Publisher Index Page"},{"id":355021,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -104.67773437499999,\n 26.667095801104814\n ],\n [\n -92.98828125,\n 26.667095801104814\n ],\n [\n -92.98828125,\n 43.644025847699496\n ],\n [\n -104.67773437499999,\n 43.644025847699496\n ],\n [\n -104.67773437499999,\n 26.667095801104814\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"9","issue":"1","publishingServiceCenter":{"id":9,"text":"Reston PSC"},"noUsgsAuthors":false,"publicationDate":"2018-01-04","publicationStatus":"PW","scienceBaseUri":"5b46e568e4b060350a15d127","contributors":{"authors":[{"text":"Andersson, Kent","contributorId":205605,"corporation":false,"usgs":false,"family":"Andersson","given":"Kent","affiliations":[],"preferred":false,"id":737939,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Davis, Craig A.","contributorId":171490,"corporation":false,"usgs":false,"family":"Davis","given":"Craig","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":737940,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Harris, Grant","contributorId":172342,"corporation":false,"usgs":false,"family":"Harris","given":"Grant","affiliations":[],"preferred":false,"id":737941,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Haukos, David A. 0000-0001-5372-9960 dhaukos@usgs.gov","orcid":"https://orcid.org/0000-0001-5372-9960","contributorId":3664,"corporation":false,"usgs":true,"family":"Haukos","given":"David","email":"dhaukos@usgs.gov","middleInitial":"A.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true},{"id":198,"text":"Coop Res Unit Atlanta","active":true,"usgs":true}],"preferred":true,"id":737936,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70197615,"text":"70197615 - 2018 - Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species","interactions":[],"lastModifiedDate":"2018-11-14T09:57:14","indexId":"70197615","displayToPublicDate":"2018-06-13T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1018,"text":"Biological Invasions","active":true,"publicationSubtype":{"id":10}},"title":"Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species","docAbstract":"Knowledge of the spatial distributions and dispersal characteristics of invasive species is necessary for managing the spread of highly mobile species, such as invasive bigheaded carps (Bighead Carp [Hypophthalmichthys nobilis] and Silver Carp [H. molitrix]). Management of invasive bigheaded carps in the Illinois River has focused on using human-made barriers and harvest to limit dispersal towards the Laurentian Great Lakes. Acoustic telemetry data were used to parameterize multistate models to examine the spatial dynamics of bigheaded carps in the Illinois River to (1) evaluate the effects of existing dams on movement, (2) identify how individuals distribute among pools, and (3) gauge the effects of reductions in movement towards the invasion front. Multistate models estimated that movement was generally less likely among upper river pools (Starved Rock, Marseilles, and Dresden Island) than the lower river (La Grange and Peoria) which matched the pattern of gated versus wicket style dams. Simulations using estimated movement probabilities indicated that Bighead Carp accumulate in La Grange Pool while Silver Carp accumulate in Alton Pool. Fewer Bighead Carp reached the upper river compared to Silver Carp during simulations. Reducing upstream movement probabilities (e.g., reduced propagule pressure) by ≥ 75% into any of the upper river pools could reduce upper river abundance with similar results regardless of location. Given bigheaded carp reproduction in the upper Illinois River is presently limited, reduced movement towards the invasion front coupled with removal of individuals reaching these areas could limit potential future dispersal towards the Great Lakes.
","language":"English","publisher":"Springer","doi":"10.1007/s10530-018-1772-6","usgsCitation":"Coulter, A.A., Brey, M.K., Lubejko, M., Kallis, J.L., Coulter, D.P., Glover, D.C., Whitledge, G.W., and Garvey, J.E., 2018, Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species: Biological Invasions, v. 20, no. 11, p. 3255-3270, https://doi.org/10.1007/s10530-018-1772-6.","productDescription":"16 p.","startPage":"3255","endPage":"3270","ipdsId":"IP-086127","costCenters":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"links":[{"id":437866,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9RYXNS4","text":"USGS data release","linkHelpText":"Multistate models of bigheaded carps in the Illinois River reveal spatial dynamics of invasive species: Data"},{"id":355022,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","otherGeospatial":"Laurentian Great Lakes","volume":"20","issue":"11","publishingServiceCenter":{"id":15,"text":"Madison PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-05","publicationStatus":"PW","scienceBaseUri":"5b46e569e4b060350a15d129","contributors":{"authors":[{"text":"Coulter, Alison A.","contributorId":187652,"corporation":false,"usgs":false,"family":"Coulter","given":"Alison","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":737930,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brey, Marybeth K. 0000-0003-4403-9655 mbrey@usgs.gov","orcid":"https://orcid.org/0000-0003-4403-9655","contributorId":187651,"corporation":false,"usgs":true,"family":"Brey","given":"Marybeth","email":"mbrey@usgs.gov","middleInitial":"K.","affiliations":[{"id":606,"text":"Upper Midwest Environmental Sciences Center","active":true,"usgs":true}],"preferred":true,"id":737929,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lubejko, Matthew","contributorId":195897,"corporation":false,"usgs":false,"family":"Lubejko","given":"Matthew","email":"","affiliations":[],"preferred":false,"id":737931,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kallis, Jahn L.","contributorId":205603,"corporation":false,"usgs":false,"family":"Kallis","given":"Jahn","email":"","middleInitial":"L.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":737932,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Coulter, David P.","contributorId":205629,"corporation":false,"usgs":false,"family":"Coulter","given":"David","email":"","middleInitial":"P.","affiliations":[],"preferred":false,"id":737999,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Glover, David C.","contributorId":178006,"corporation":false,"usgs":false,"family":"Glover","given":"David","email":"","middleInitial":"C.","affiliations":[],"preferred":false,"id":737933,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Garvey, James E.","contributorId":178007,"corporation":false,"usgs":false,"family":"Garvey","given":"James","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":737935,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Whitledge, Gregory W.","contributorId":205604,"corporation":false,"usgs":false,"family":"Whitledge","given":"Gregory","email":"","middleInitial":"W.","affiliations":[{"id":32417,"text":"Southern Illinois University-Carbondale","active":true,"usgs":false}],"preferred":false,"id":737934,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70227956,"text":"70227956 - 2018 - Large-scale variation in density of an aquatic ecosystem indicator species","interactions":[],"lastModifiedDate":"2022-02-02T15:47:17.939692","indexId":"70227956","displayToPublicDate":"2018-06-12T09:37:25","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3358,"text":"Scientific Reports","active":true,"publicationSubtype":{"id":10}},"title":"Large-scale variation in density of an aquatic ecosystem indicator species","docAbstract":"Monitoring indicator species is a pragmatic approach to natural resource assessments, especially when the link between the indicator species and ecosystem state is well justified. However, conducting ecosystem assessments over representative spatial scales that are insensitive to local heterogeneity is challenging. We examine the link between polychlorinated biphenyl (PCB) contamination and population density of an aquatic habitat specialist over a large spatial scale using non-invasive genetic spatial capture-recapture. Using American mink (Neovison vison), a predatory mammal and an indicator of aquatic ecosystems, we compared estimates of density in two major river systems, one with extremely high levels of PCB contamination (Hudson River), and a hydrologically independent river with lower PCB levels (Mohawk River). Our work supports the hypothesis that the mink densities are substantially (1.64-1.67 times) lower in the contaminated river system. We demonstrate the value of coupling the indicator species concept with well-conceived and spatially representative monitoring protocols. PCBs have demonstrable detrimental effects on aquatic ecosystems, including mink, and these effects are likely to be profound and long-lasting, manifesting as population-level impacts. Through integrating non-invasive data collection, genetic analysis, and spatial capture-recapture methods, we present a monitoring framework for generating robust density estimates across large spatial scales.","language":"English","publisher":"Nature Publishing Group","doi":"10.1038/s41598-018-26847-x","usgsCitation":"Sutherland, C., Fuller, A.K., Royle, A., Hare, M.P., and Madden, S., 2018, Large-scale variation in density of an aquatic ecosystem indicator species: Scientific Reports, v. 8, p. 1-10, https://doi.org/10.1038/s41598-018-26847-x.","productDescription":"8958, 10 p.","startPage":"1","endPage":"10","ipdsId":"IP-094157","costCenters":[{"id":199,"text":"Coop Res Unit Leetown","active":true,"usgs":true},{"id":531,"text":"Patuxent Wildlife Research Center","active":true,"usgs":true}],"links":[{"id":468667,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1038/s41598-018-26847-x","text":"Publisher Index Page"},{"id":395271,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New York","otherGeospatial":"Hudson River, Mohawk River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -74.39666748046874,\n 41.044145364313174\n ],\n [\n -73.43536376953125,\n 41.044145364313174\n ],\n [\n -73.43536376953125,\n 43.31718491566705\n ],\n [\n -74.39666748046874,\n 43.31718491566705\n ],\n [\n -74.39666748046874,\n 41.044145364313174\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"8","noUsgsAuthors":false,"publicationDate":"2018-06-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Sutherland, Chris","contributorId":245389,"corporation":false,"usgs":false,"family":"Sutherland","given":"Chris","affiliations":[{"id":49181,"text":"Univ. 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We used a novel camera trap method to evaluate the accuracy of gridded snow data in a mountainous region of the northeastern US. We were specifically interested in assessing (1) how snow depth observations from remote cameras compare with gridded climate data, (2) the sources of error associated with the gridded data and (3) the influence of spatial sampling on bias. We compared daily observations recorded by remote cameras with Snow Data Assimilation System (SNODAS ) gridded predictions using data from three winters (2014–2016). Snow depth observations were correlated with SNODAS predictions for sites (R 2 = 0.20) and regions (R 2 = 0.16), yet we detected factors associated with SNODAS bias at both scales. Specifically, SNODAS underpredicted depths at high elevations, at sites with higher solar radiation, and within conifer‐dominated forest. Depths were most underpredicted at highest elevations, up to 44 and 26 cm on average at the site and region scales, respectively. Bias was greatest when predictions were lowest, occasionally predicting snow absence when depths were >100 cm at camera sites. We also detected breakdowns in accuracy when certain environmental conditions varied within the 1 km2 SNODAS grid cells. For example, underprediction was greatest when the solar radiation values of camera stations increased relative to the mean of the SNODAS grid cells. This relationship was most prominent in mountainous regions, suggesting that factors which influence solar radiation (e.g. topographic complexity) contribute to SNODAS inaccuracy. We caution using gridded snow data for ecological studies when bias is unknown. We suggest increased sampling to adjust for errors associated with gridded data products that arise from factors, such as forest cover and topographic variability. Increasing resolution and accuracy of climate data will improve predictions of species’ responses to climate change.
","language":"English","publisher":"Wiley","doi":"10.1002/rse2.85","usgsCitation":"Siren, A.P., Somos-Valenzuela, M., Callahan, C., Kilborn, J.R., Duclos, T., Tragert, C., and Morelli, T.L., 2018, Looking beyond wildlife: Using remote cameras to evaluate accuracy of gridded snow data: Remote Sensing in Ecology and Conservation, v. 4, no. 4, p. 375-386, https://doi.org/10.1002/rse2.85.","productDescription":"12 p.","startPage":"375","endPage":"386","ipdsId":"IP-097034","costCenters":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true}],"links":[{"id":468668,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/rse2.85","text":"Publisher Index Page"},{"id":376820,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"New Hampshire, Vermont","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -72.432861328125,\n 43.01268088642034\n ],\n [\n -70.9222412109375,\n 43.329173667843904\n ],\n [\n -71.08154296875,\n 45.29421101337773\n ],\n [\n -71.1419677734375,\n 45.24782097102814\n ],\n [\n -71.2408447265625,\n 45.282617057517406\n ],\n [\n -71.4825439453125,\n 44.94536144236941\n ],\n [\n -72.09228515625,\n 44.63739123445585\n ],\n [\n -72.3065185546875,\n 43.878097874251736\n ],\n [\n -72.432861328125,\n 43.01268088642034\n ]\n ]\n ]\n }\n }\n ]\n}","volume":"4","issue":"4","noUsgsAuthors":false,"publicationDate":"2018-06-11","publicationStatus":"PW","contributors":{"authors":[{"text":"Siren, Alexej P.K. 0000-0003-3067-6418","orcid":"https://orcid.org/0000-0003-3067-6418","contributorId":236777,"corporation":false,"usgs":false,"family":"Siren","given":"Alexej","email":"","middleInitial":"P.K.","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794315,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Somos-Valenzuela, Marcelo 0000-0001-7863-4407","orcid":"https://orcid.org/0000-0001-7863-4407","contributorId":236778,"corporation":false,"usgs":false,"family":"Somos-Valenzuela","given":"Marcelo","email":"","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794316,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Callahan, Catherine","contributorId":236779,"corporation":false,"usgs":false,"family":"Callahan","given":"Catherine","email":"","affiliations":[{"id":47548,"text":"Universidad de La Frontera, Temuco, Chile","active":true,"usgs":false}],"preferred":false,"id":794317,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Kilborn, Jillian R.","contributorId":236780,"corporation":false,"usgs":false,"family":"Kilborn","given":"Jillian","email":"","middleInitial":"R.","affiliations":[{"id":47548,"text":"Universidad de La Frontera, Temuco, Chile","active":true,"usgs":false}],"preferred":false,"id":794318,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duclos, Timothy","contributorId":236781,"corporation":false,"usgs":false,"family":"Duclos","given":"Timothy","email":"","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794319,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Tragert, Cassie","contributorId":236782,"corporation":false,"usgs":false,"family":"Tragert","given":"Cassie","email":"","affiliations":[{"id":41510,"text":"Department of Environmental Conservation, University of Massachusetts","active":true,"usgs":false}],"preferred":false,"id":794320,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Morelli, Toni Lyn 0000-0001-5865-5294 tmorelli@usgs.gov","orcid":"https://orcid.org/0000-0001-5865-5294","contributorId":197458,"corporation":false,"usgs":true,"family":"Morelli","given":"Toni","email":"tmorelli@usgs.gov","middleInitial":"Lyn","affiliations":[{"id":5080,"text":"Northeast Climate Adaptation Science Center","active":true,"usgs":true},{"id":411,"text":"National Climate Change and Wildlife Science Center","active":true,"usgs":true}],"preferred":true,"id":794321,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70197533,"text":"70197533 - 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dhondorp@usgs.gov","orcid":"https://orcid.org/0000-0002-5182-1963","contributorId":5376,"corporation":false,"usgs":true,"family":"Hondorp","given":"Darryl","email":"dhondorp@usgs.gov","middleInitial":"W.","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737576,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Nate, Nancy","contributorId":205503,"corporation":false,"usgs":false,"family":"Nate","given":"Nancy","affiliations":[{"id":6601,"text":"Michigan State University","active":true,"usgs":false}],"preferred":false,"id":737577,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Paige, Kelli","contributorId":205504,"corporation":false,"usgs":false,"family":"Paige","given":"Kelli","email":"","affiliations":[{"id":37112,"text":"Great Lakes Observing System","active":true,"usgs":false}],"preferred":false,"id":737578,"contributorType":{"id":1,"text":"Authors"},"rank":8},{"text":"Riley, Stephen 0000-0002-8968-8416 sriley@usgs.gov","orcid":"https://orcid.org/0000-0002-8968-8416","contributorId":169479,"corporation":false,"usgs":true,"family":"Riley","given":"Stephen","email":"sriley@usgs.gov","affiliations":[{"id":324,"text":"Great Lakes Science Center","active":true,"usgs":true}],"preferred":true,"id":737579,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Fisk, Aaron T.","contributorId":127340,"corporation":false,"usgs":false,"family":"Fisk","given":"Aaron","email":"","middleInitial":"T.","affiliations":[{"id":6778,"text":"University of Windsor, Windsor, Ontario, Canada","active":true,"usgs":false}],"preferred":false,"id":737580,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Cooke, Steven J.","contributorId":56132,"corporation":false,"usgs":false,"family":"Cooke","given":"Steven J.","affiliations":[{"id":36574,"text":"Carleton University, Ottawa, Ontario","active":true,"usgs":false}],"preferred":false,"id":737581,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70197734,"text":"70197734 - 2018 - Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology","interactions":[],"lastModifiedDate":"2018-06-19T17:03:05","indexId":"70197734","displayToPublicDate":"2018-06-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":24,"text":"Conference Paper"},"publicationSubtype":{"id":19,"text":"Conference Paper"},"title":"Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology","docAbstract":"Following dam installations in the remote Rainy Lake Basin during the early 1900s, water-level fluctuations were considered extreme (1914–1949) compared to more natural conditions. In 1949, the International Joint Commission (IJC), which sets rules governing dam operation on waters shared by the United States and Canada, established the first rule curves to regulate water levels on these waterbodies. However, rule curves established prior to 2000 were determined to be detrimental to the ecosystem. Therefore, the IJC implemented an order in 2000 to change rule curves and to restore a more natural water regime. After 2000, measured chlorophyll-a concentrations in the two most eutrophic water bodies decreased whereas concentrations in oligotrophic lakes did not show significant water-quality differences. Fish mercury data were inconclusive, due to the variation in water levels and fish mercury concentrations, but can be used by the IJC as part of a long term data set.
","largerWorkType":{"id":4,"text":"Book"},"largerWorkTitle":"World Environmental and Water Resources Congress 2018","largerWorkSubtype":{"id":12,"text":"Conference publication"},"conferenceTitle":"World Environmental and Water Resources Congress 2018","conferenceDate":"June 3-7, 2018","conferenceLocation":"Minneapolis, MN","language":"English","publisher":"ASCE","doi":"10.1061/9780784481394.017","usgsCitation":"Christensen, V.G., Maki, R., and LeDuc, J.F., 2018, Voyageurs National Park: Water-level regulation and effects on water quality and aquatic biology, in World Environmental and Water Resources Congress 2018, Minneapolis, MN, June 3-7, 2018, https://doi.org/10.1061/9780784481394.017.","ipdsId":"IP-093049","costCenters":[{"id":392,"text":"Minnesota Water Science Center","active":true,"usgs":true}],"links":[{"id":355183,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Minnesota","otherGeospatial":"Voyageurs","publishingServiceCenter":{"id":4,"text":"Rolla PSC"},"noUsgsAuthors":false,"publicationDate":"2018-05-31","publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d141","contributors":{"authors":[{"text":"Christensen, Victoria G. 0000-0003-4166-7461 vglenn@usgs.gov","orcid":"https://orcid.org/0000-0003-4166-7461","contributorId":2354,"corporation":false,"usgs":true,"family":"Christensen","given":"Victoria","email":"vglenn@usgs.gov","middleInitial":"G.","affiliations":[{"id":37947,"text":"Upper Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":738323,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Maki, Ryan P.","contributorId":100111,"corporation":false,"usgs":true,"family":"Maki","given":"Ryan P.","affiliations":[],"preferred":false,"id":738324,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"LeDuc, Jaime F.","contributorId":190132,"corporation":false,"usgs":false,"family":"LeDuc","given":"Jaime","email":"","middleInitial":"F.","affiliations":[],"preferred":false,"id":738325,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70198019,"text":"70198019 - 2018 - GIS-based method for estimating surficial groundwater levels in coastal Virginia using limited information","interactions":[],"lastModifiedDate":"2018-07-16T11:09:37","indexId":"70198019","displayToPublicDate":"2018-06-11T00:00:00","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2362,"text":"Journal of Irrigation and Drainage Engineering","active":true,"publicationSubtype":{"id":10}},"title":"GIS-based method for estimating surficial groundwater levels in coastal Virginia using limited information","docAbstract":"In many coastal areas, high water tables are present, complicating installation of some stormwater best management practices (BMPs) that rely on infiltration. Regional estimates of the seasonal high water table (SHWT) often rely on sources such as soil surveys taken over a decade ago; these data are static and do not account for groundwater withdrawals or other anthropogenic impacts. To improve estimates of the SHWT, we developed a GIS-based methodology relying on surface water elevations. Data sources included a 1.5-m (5.0 ft) resolution Lidar-derived digital elevation model (DEM), aerial imagery, and publicly available shapefiles of water boundaries. Twenty-six groundwater monitoring wells were screened to eliminate well locations influenced by pumping, yielding 22 wells. In coastal Virginia, tidal water bodies and ditches form terminal boundaries for discharge from the water-table aquifers and permit water table elevations to be fixed at the landward boundaries of surface water bodies. Water table elevations interpolated from well data and boundary elevations were used to create a triangulated irregular network representing the water table elevations for November 2012, which was the date of the DEM. An adjustment factor, calculated from the highest recorded April water table depth from long-term groundwater monitoring data, was added to estimate the SHWT elevation. SHWT elevations were subtracted from the DEM to yield SHWT depth, which was compared with long-term monitoring well data, yielding an R2 value of 0.91. Residual errors were random, although the method underpredicted the highest expected SHWT and overpredicted the median SHWT. The SHWT depth map was validated by using water table depths from 57 soil borings at 10 different sites, and consistently matched observations better than available soil survey estimates. The SHWT depth map could be useful for BMP siting and feasibility studies in similar hydrogeological settings.
","language":"English","publisher":"ASCE","doi":"10.1061/(ASCE)IR.1943-4774.0001313","usgsCitation":"Johnson, R., Sample, D., and McCoy, K.J., 2018, GIS-based method for estimating surficial groundwater levels in coastal Virginia using limited information: Journal of Irrigation and Drainage Engineering, v. 144, no. 7, p. 1-14, https://doi.org/10.1061/(ASCE)IR.1943-4774.0001313.","productDescription":"Article 05018004; 14 p.","startPage":"1","endPage":"14","ipdsId":"IP-075767","costCenters":[{"id":614,"text":"Virginia Water Science Center","active":true,"usgs":true},{"id":642,"text":"West Virginia Water Science Center","active":true,"usgs":true},{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"links":[{"id":468670,"rank":0,"type":{"id":41,"text":"Open Access External Repository Page"},"url":"https://doi.org/10.1061/(asce)ir.1943-4774.0001313","text":"External Repository"},{"id":355518,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Virginia","volume":"144","issue":"7","noUsgsAuthors":false,"publicationStatus":"PW","scienceBaseUri":"5b46e56de4b060350a15d13f","contributors":{"authors":[{"text":"Johnson, R.D.","contributorId":62360,"corporation":false,"usgs":true,"family":"Johnson","given":"R.D.","email":"","affiliations":[],"preferred":false,"id":739631,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Sample, David J.","contributorId":204837,"corporation":false,"usgs":false,"family":"Sample","given":"David J.","affiliations":[{"id":36990,"text":"Virginia Tech Biological Systems Engineering Department","active":true,"usgs":false}],"preferred":false,"id":739630,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"McCoy, Kurt J. 0000-0002-9756-8238 kjmccoy@usgs.gov","orcid":"https://orcid.org/0000-0002-9756-8238","contributorId":1391,"corporation":false,"usgs":true,"family":"McCoy","given":"Kurt","email":"kjmccoy@usgs.gov","middleInitial":"J.","affiliations":[{"id":37280,"text":"Virginia and West Virginia Water Science Center ","active":true,"usgs":true}],"preferred":true,"id":739632,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70221334,"text":"70221334 - 2018 - Ground-nesting great horned owl in Suisun Marsh, California","interactions":[],"lastModifiedDate":"2021-06-10T12:28:18.88242","indexId":"70221334","displayToPublicDate":"2018-06-10T07:24:53","publicationYear":"2018","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1153,"text":"California Fish and Game","active":true,"publicationSubtype":{"id":10}},"title":"Ground-nesting great horned owl in Suisun Marsh, California","docAbstract":"Great horned owls (Bubo virginianus) are widespread throughout North, Central, and parts of South America (Artuso et al. 2013). Across this range, great horned owls are generalists, occupying a diverse range of habitats including deciduous and coniferous forests, wetlands, and agricultural landscapes. Within these habitats, great horned owls are generally found near upland or short-vegetation habitat suitable for locating prey (Artuso et al. 2013). In Suisun Marsh, California, great horned owls primarily occupy stands of non-native eucalyptus (Eucalyptus spp.), as well as man-made structures like waterfowl-nesting platforms (Figure 1) and on dock pilings over water (Figure 2), and they forage in nearby upland fields and seasonally flooded, diked wetlands managed primarily for waterfowl (USGS unpublished data).","language":"English","publisher":"California Department of Fish and Wildlife","usgsCitation":"Skalos, S., Falcon, M.J., Wang, O., Mott, A.L., Hunt, M., Rocha, O., Ackerman, J.T., Casazza, M.L., and Hull, J.M., 2018, Ground-nesting great horned owl in Suisun Marsh, California: California Fish and Game, v. 104, no. 4, p. 164-172.","productDescription":"9 p.","startPage":"164","endPage":"172","ipdsId":"IP-101149","costCenters":[{"id":651,"text":"Western Ecological Research 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sskalos@usgs.gov","orcid":"https://orcid.org/0000-0003-1229-8580","contributorId":167191,"corporation":false,"usgs":true,"family":"Skalos","given":"Shannon","email":"sskalos@usgs.gov","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817352,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Falcon, Matthew J.","contributorId":260146,"corporation":false,"usgs":false,"family":"Falcon","given":"Matthew","email":"","middleInitial":"J.","affiliations":[{"id":39913,"text":"former WERC","active":true,"usgs":false}],"preferred":false,"id":817353,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Wang, Olivia","contributorId":260147,"corporation":false,"usgs":false,"family":"Wang","given":"Olivia","email":"","affiliations":[{"id":52524,"text":"University of California, Davis, Department of Animal Science, 1 Shields Avenue, Davis, CA 95616, USA (SS, OW, 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Wildlife, Grizzly Island Wildlife Area, 2548 Grizzly Island Road, Suisun City, CA 94585, USA (OR)","active":true,"usgs":false}],"preferred":false,"id":817357,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Ackerman, Joshua T. 0000-0002-3074-8322","orcid":"https://orcid.org/0000-0002-3074-8322","contributorId":202848,"corporation":false,"usgs":true,"family":"Ackerman","given":"Joshua","middleInitial":"T.","affiliations":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"preferred":true,"id":817358,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Casazza, Michael L. 0000-0002-5636-735X mike_casazza@usgs.gov","orcid":"https://orcid.org/0000-0002-5636-735X","contributorId":2091,"corporation":false,"usgs":true,"family":"Casazza","given":"Michael","email":"mike_casazza@usgs.gov","middleInitial":"L.","affiliations":[{"id":651,"text":"Western Ecological Research 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Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-1057","title":"Preliminary geologic framework developed for a proposed environmental monitoring study of a deep, unconventional Marcellus Shale drill site, Washington County, Pennsylvania","docAbstract":"In the fall of 2011, the U.S. Geological Survey (USGS) was afforded an opportunity to participate in an environmental monitoring study of the potential impacts of a deep, unconventional Marcellus Shale hydraulic fracturing site. The drill site of the prospective case study is the “Range Resources MCC Partners L.P. Units 1-5H” location (also referred to as the “RR–MCC” drill site), located in Washington County, southwestern Pennsylvania. Specifically, the USGS was approached to provide a geologic framework that would (1) provide geologic parameters for the proposed area of a localized groundwater circulation model, and (2) provide potential information for the siting of both shallow and deep groundwater monitoring wells located near the drill pad and the deviated drill legs.
The lead organization of the prospective case study of the RR–MCC drill site was the Groundwater and Ecosystems Restoration Division (GWERD) of the U.S. Environmental Protection Agency. Aside from the USGS, additional partners/participants were to include the Department of Energy, the Pennsylvania Geological Survey, the Pennsylvania Department of Environmental Protection, and the developer Range Resources LLC. During the initial cooperative phase, GWERD, with input from the participating agencies, drafted a Quality Assurance Project Plan (QAPP) that proposed much of the objectives, tasks, sampling and analytical procedures, and documentation of results.
Later in 2012, the proposed cooperative agreement between the aforementioned partners and the associated land owners for a monitoring program at the drill site was not executed. Therefore, the prospective case study of the RR–MCC site was terminated and no installation of groundwater monitoring wells nor the collection of nearby soil, stream sediment, and surface-water samples were made.
Prior to the completion of the QAPP and termination of the perspective case study the geologic framework was rapidly conducted and nearly completed. This was done for three principal reasons. First, there was an immediate need to know the distribution of the relatively undisturbed surface to near-surface bedrock geology and unconsolidated materials for the collection of baseline surface data prior to drill site development (drill pad access road, drill pad leveling) and later during monitoring associated with well drilling, well development, and well production. Second, it was necessary to know the bedrock geology to support the siting of: (1) multiple shallow groundwater monitoring wells (possibly as many as four) surrounding and located immediately adjacent to the drill pad, and (2) deep groundwater monitoring wells (possibly two) located at distance from the drill pad with one possibly being sited along one of the deviated production drill legs. Lastly, the framework geology would provide the lateral extent, thickness, lithology, and expected discontinuities of geologic units (to be parsed or grouped as hydrostratigraphic units) and regional structure trends as inputs into the groundwater model.
This report provides the methodology of geologic data accumulation and aggregation, and its integration into a geographic information system (GIS) based program. The GIS program will allow multiple data to be exported in various formats (shapefiles [.shp], database files [.dbf], and Keyhole Markup Language files [.KML]) for use in surface and subsurface geologic site characterization, for sampling strategies, and for inputs for groundwater modeling.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181057","usgsCitation":"Stamm, R.G., 2018, Preliminary geologic framework developed for a proposed environmental monitoring study of a deep, unconventional Marcellus Shale drill site, Washington County, Pennsylvania: U.S. Geological Survey Open-File Report 2018–1057, 49 p., https://doi.org/10.3133/ofr20181057.","productDescription":"vi, 49 p.","numberOfPages":"59","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-069591","costCenters":[{"id":243,"text":"Eastern Geology and Paleoclimate Science Center","active":true,"usgs":true}],"links":[{"id":354769,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1057/ofr20181057.pdf","text":"Report","size":"129 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1057"},{"id":354768,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1057/coverthb.jpg"}],"country":"United States","state":"Pennsylvania","county":"Washington County","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"type\": \"Polygon\",\n \"coordinates\": [\n [\n [\n -80.4833,\n 40.3\n ],\n [\n -80.3833,\n 40.3\n ],\n [\n -80.3833,\n 40.3833\n ],\n [\n -80.4833,\n 40.3833\n ],\n [\n -80.4833,\n 40.3\n ]\n ]\n ]\n }\n }\n ]\n}","contact":"Eastern Geology and Paleoclimate Science Center
U.S. Geological Survey
926A National Center
12201 Sunrise Valley Drive
Reston, VA 20192
A review is given of the present feasibility for accurately mapping geoelectric fields across North America in near-realtime by modeling geomagnetic monitoring and magnetotelluric survey data. Should this capability be successfully developed, it could inform utility companies of magnetic-storm interference on electric-power-grid systems. That real-time mapping of geoelectric fields is a challenge is reflective of (1) the spatiotemporal complexity of geomagnetic variation, especially during magnetic storms, (2) the sparse distribution of ground-based geomagnetic monitoring stations that report data in realtime, (3) the spatial complexity of three-dimensional solid-Earth impedance, and (4) the geographically incomplete state of continental-scale magnetotelluric surveys.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20181043","usgsCitation":"Love, J.J., Rigler, E.J., Kelbert, Anna, Finn, C.A., Bedrosian, P.A., and Balch, C.C., 2018, On the feasibility of real-time mapping of the geoelectric field across North America: U.S. Geological Survey Open-File Report 2018-1043, 16 p., https://doi.org/10.3133/ofr20181043.","productDescription":"v, 16 p.","numberOfPages":"26","onlineOnly":"Y","ipdsId":"IP-093233","costCenters":[{"id":300,"text":"Geologic Hazards Science Center","active":true,"usgs":true}],"links":[{"id":354843,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2018/1043/coverthb.jpg"},{"id":354844,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2018/1043/ofr20181043.pdf","text":"Report","size":"1.45 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2018-1043"}],"contact":"Director, Geologic Hazards Science Center
U.S. Geological Survey
Box 25046, Mail Stop 966
Denver, CO 80225
Plant‐mediated processes determine carbon (C) cycling and storage in many ecosystems; how plant‐associated processes may be altered by climate‐induced changes in environmental drivers is therefore an essential question for understanding global C cycling. In this study, we hypothesize that environmental alterations associated with near‐term climate change can exert strong control on plant‐associated ecosystem C cycling and that investigations along an extended hydrologic gradient may give mechanistic insight into C cycling. We utilize a mesocosm approach to investigate the response of plant, soil, and gaseous C cycling to changing hydrologic regimes and elevated atmospheric carbon dioxide (CO2) concentrations expected by 2100 in a coastal salt marsh in Louisiana, USA. Although elevated CO2 had no significant effects on C cycling, we demonstrate that greater average flooding depth stimulated C exchange, with higher rates of labile C decomposition, plant CO2 assimilation, and soil C respiration. Greater average flooding depth also significantly decreased the soil C pool and marginally increased the aboveground biomass C pool, leading to net losses in total C stocks. Further, flooding depths along an extended hydrologic gradient garnered insight into decomposition mechanisms that was not apparent from other data. In C‐4 dominated salt marshes, sea‐level rise will likely overwhelm effects of elevated CO2 with climate change. Deeper flooding associated with sea‐level rise may decrease long‐term soil C pools and quicken C exchange between soil and atmosphere, thereby threatening net C storage in salt marsh habitats. Manipulative studies will be indispensable for understanding biogeochemical cycling under future conditions.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2017JG004369","usgsCitation":"Jones, S., Stagg, C.L., Hester, M.W., and Krauss, K.W., 2018, Flooding alters plant-mediated carbon cycling independently of elevated atmospheric CO2 concentrations: Journal of Geophysical Research: Biogeosciences, v. 123, no. 6, p. 1976-1987, https://doi.org/10.1029/2017JG004369.","productDescription":"12 p.","startPage":"1976","endPage":"1987","ipdsId":"IP-091480","costCenters":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"links":[{"id":460897,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2017jg004369","text":"Publisher Index Page"},{"id":437869,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7NK3D7M","text":"USGS data release","linkHelpText":"Salt marsh carbon dynamics under altered hydrologic regimes and elevated CO2 conditions, Louisiana, USA (2014-2015)"},{"id":355626,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"123","issue":"6","publishingServiceCenter":{"id":5,"text":"Lafayette PSC"},"noUsgsAuthors":false,"publicationDate":"2018-06-29","publicationStatus":"PW","scienceBaseUri":"5b46e56ee4b060350a15d14d","contributors":{"authors":[{"text":"Jones, Scott F. 0000-0002-1056-3785","orcid":"https://orcid.org/0000-0002-1056-3785","contributorId":204137,"corporation":false,"usgs":false,"family":"Jones","given":"Scott F.","affiliations":[{"id":36864,"text":"University of Louisiana Lafayette","active":true,"usgs":false}],"preferred":false,"id":739900,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stagg, Camille L. 0000-0002-1125-7253 staggc@usgs.gov","orcid":"https://orcid.org/0000-0002-1125-7253","contributorId":4111,"corporation":false,"usgs":true,"family":"Stagg","given":"Camille","email":"staggc@usgs.gov","middleInitial":"L.","affiliations":[{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true},{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true}],"preferred":true,"id":739795,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Krauss, Ken W. 0000-0003-2195-0729 kraussk@usgs.gov","orcid":"https://orcid.org/0000-0003-2195-0729","contributorId":2017,"corporation":false,"usgs":true,"family":"Krauss","given":"Ken","email":"kraussk@usgs.gov","middleInitial":"W.","affiliations":[{"id":17705,"text":"Wetland and Aquatic Research Center","active":true,"usgs":true},{"id":455,"text":"National Wetlands Research Center","active":true,"usgs":true}],"preferred":true,"id":739796,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hester, Mark W.","contributorId":195572,"corporation":false,"usgs":false,"family":"Hester","given":"Mark","email":"","middleInitial":"W.","affiliations":[{"id":34316,"text":"University of Louisiana at Lafayette, Lafayette, LA, USA","active":true,"usgs":false}],"preferred":false,"id":739797,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70196681,"text":"sir20185060 - 2018 - Water-quality observations of the San Antonio segment of the Edwards aquifer, Texas, with an emphasis on processes influencing nutrient and pesticide geochemistry and factors affecting aquifer vulnerability, 2010–16","interactions":[],"lastModifiedDate":"2018-06-08T10:15:09","indexId":"sir20185060","displayToPublicDate":"2018-06-07T13:45:00","publicationYear":"2018","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2018-5060","title":"Water-quality observations of the San Antonio segment of the Edwards aquifer, Texas, with an emphasis on processes influencing nutrient and pesticide geochemistry and factors affecting aquifer vulnerability, 2010–16","docAbstract":"As questions regarding the influence of increasing urbanization on water quality in the Edwards aquifer are raised, a better understanding of the sources, fate, and transport of compounds of concern in the aquifer—in particular, nutrients and pesticides—is needed to improve water management decision-making capabilities. The U.S. Geological Survey, in cooperation with the San Antonio Water System, performed a study from 2010 to 2016 to better understand how water quality changes under a range of hydrologic conditions and in contrasting land-cover settings (rural and urban) in the Edwards aquifer. The study design included continuous hydrologic monitoring, continuous water-quality monitoring, and discrete sample collection for a detailed characterization of water quality at a network of sites throughout the aquifer system. The sites were selected to encompass a “source-to-sink” (that is, from aquifer recharge to aquifer discharge) approach. Network sites were selected to characterize rainfall, recharging surface water, and groundwater; groundwater sites included wells in the unconfined part of the aquifer (unconfined wells) and in the confined part of the aquifer (confined wells) and a major discharging spring. Storm-related samples—including rainfall samples, stormwater-runoff (surface-water) samples, and groundwater samples—were collected to characterize the aquifer response to recharge.
Elevated nitrate concentrations relative to national background values and the widespread detection of pesticides indicate that the Edwards aquifer is vulnerable to contamination and that vulnerability is affected by factors such as land cover, aquifer hydrogeology, and changes in hydrologic conditions. Greater vulnerability of groundwater in urban areas relative to rural areas was evident from results for urban groundwater sites, which generally had higher nitrate concentrations, elevated δ15N-nitrate values, a greater diversity of pesticides, and higher pesticide concentrations. The continuum of water quality from unconfined rural groundwater sites (least affected by anthropogenic contamination) to unconfined urban groundwater sites (most affected by anthropogenic contamination) demonstrates enhanced vulnerability of urban versus rural land cover. Differences in contaminant occurrences and concentration among unconfined urban wells indicate that the urban parts of the aquifer are not uniformly vulnerable, but rather are affected by spatial differences in the sources of nutrients and pesticides. In urban areas, the shallow, unconfined groundwater sites showed greater temporal variability in both nutrient and pesticide concentrations, as well as a greater degree of contamination, than did deeper, confined groundwater sites. In comparison to that of the shallow, unconfined groundwater sites, the water quality of the deeper, confined groundwater sites was relatively invariant during this multiyear study. Although aquifer hydrogeology is an important factor related to aquifer vulnerability, land cover likely has a greater influence on pesticide contamination of groundwater. Temporal variability in hydrologic conditions for the Edwards aquifer is apparent in data for surface water as a source of groundwater recharge, water-level altitude in wells, spring discharge, and groundwater quality. This temporal variability affects recharge sources, recharge amounts, groundwater traveltimes, flow routing, water-rock interaction processes, dilution, mixing, and, in turn, water quality. Relations of land cover, aquifer hydrogeology, and changing hydrologic conditions to water quality are complex but provide insight into the vulnerability of Edwards aquifer groundwater—a vital drinking-water resource.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20185060","collaboration":"Prepared in cooperation with the San Antonio Water System","usgsCitation":"Opsahl, S.P., Musgrove, M., Mahler, B.J., and Lambert, R.B., 2018, Water-quality observations of the San Antonio segment of the Edwards aquifer, Texas, with an emphasis on processes influencing nutrient and pesticide geochemistry and factors affecting aquifer vulnerability, 2010–16: U.S. Geological Survey Scientific Investigations Report 2018–5060, 67 p., https://doi.org/10.3133/sir20185060.","productDescription":"Report: viii, 67 p.; Data release","numberOfPages":"79","onlineOnly":"N","additionalOnlineFiles":"N","ipdsId":"IP-093387","costCenters":[{"id":583,"text":"Texas Water Science Center","active":true,"usgs":true}],"links":[{"id":354772,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2018/5060/sir20185060.pdf","text":"Report","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2018-5060"},{"id":354771,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2018/5060/coverthb.jpg"},{"id":354786,"rank":3,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/F7KP81C5","text":"USGS data release","description":"USGS data release","linkHelpText":"Water-Quality Data Characterizing the San Antonio Segment of the Edwards Aquifer With an Emphasis on Processes Influencing Nutrient and Pesticide Concentrations and Factors Affecting Aquifer Vulnerability, 2010-2016"}],"country":"United States","state":"Texas","otherGeospatial":"Edwards 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Texas Water Science Center
U.S. Geological Survey
1505 Ferguson Lane
Austin, TX 78754